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SOTA
Prompt Engineering
Prompt Engineering On Oxford Iiit Pet Dataset
Prompt Engineering On Oxford Iiit Pet Dataset
평가 지표
Harmonic mean
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Harmonic mean
Paper Title
Repository
CLIP
94.12
Learning Transferable Visual Models From Natural Language Supervision
HPT++
96.91
HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
RPO
96.05
Read-only Prompt Optimization for Vision-Language Few-shot Learning
MaPLe
96.58
MaPLe: Multi-modal Prompt Learning
DePT
96.37
DePT: Decoupled Prompt Tuning
-
HPT
96.71
Learning Hierarchical Prompt with Structured Linguistic Knowledge for Vision-Language Models
ProMetaR
96.49
Prompt Learning via Meta-Regularization
MetaPrompt
96.26
Learning Domain Invariant Prompt for Vision-Language Models
PromptSRC
96.30
Self-regulating Prompts: Foundational Model Adaptation without Forgetting
CoPrompt
96.87
Consistency-guided Prompt Learning for Vision-Language Models
MMRL
96.74
MMRL: Multi-Modal Representation Learning for Vision-Language Models
CoCoOp
96.43
Conditional Prompt Learning for Vision-Language Models
PromptKD
97.15
PromptKD: Unsupervised Prompt Distillation for Vision-Language Models
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